code: def test_surrogate_error_tree_adult_census_income(self):
      dataFile = "AdultCensusIncome.csv"
      if not os.path.isfile(dataFile):
          mmlspark_url = "https://mmlspark.azureedge.net/datasets/"
          urllib.request.urlretrieve(mmlspark_url + dataFile, dataFile)
      data = spark.createDataFrame(
          pd.read_csv(dataFile, dtype={" hours-per-week": np.float64})
      )
  
      feature_names = [
          " education-num",
          " capital-gain",
          " hours-per-week",
      ]
      label_col = " income"
      data = data.select(feature_names + [label_col])
      train, test = data.randomSplit([0.75, 0.25], seed=123)
  
      assembler = (
          VectorAssembler()
          .setInputCols(feature_names)
          .setOutputCol("features")
      )
  
      indexed_label_col = "income indexed"
      indexer = StringIndexer(
          inputCol=label_col, outputCol=indexed_label_col
      )
      lr = LogisticRegression(labelCol=indexed_label_col)
  
      pipeline = Pipeline(stages=[assembler, indexer, lr])
  
      pipeline_model = pipeline.fit(train)
      categorical_features = []
      model_task = ModelTask.CLASSIFICATION
      run_error_analyzer(
          pipeline_model,
          test.to_koalas(),
          indexed_label_col,
          feature_names,
          categorical_features,
          model_task=model_task,
      )
  
file_path: responsible-ai-toolbox/erroranalysis/tests/test_pyspark_surrogate_error_tree.py
imports: import os
  import urllib
  import numpy
  import pandas
  import pytest
  from test_surrogate_error_tree import run_error_analyzer
  from erroranalysis._internal.constants import ModelTask
label_desc: Use image node_id 1 for calling the TestPysparkSurrogateErrorTree obj's underlying member method code with example usage: obj.test_surrogate_error_tree_adult_census_income() without return types